Embodiments relate to image processing, and, more particularly, to an automated technique for generating a path file of identified and extracted image features for image manipulation.
It is common practice to identify features like doors and windows from the images used in modeling and/or simulations. Identifying features in an image allows the assignment of different material codes to regions of the image. It also allows parts of the image to be selectively adjusted to create night scenes from day scenes. However, the benefits of identifying the features from an image are often overshadowed by the time-consuming nature of the processes currently available for feature identification and feature based manipulation of graphic images.
Current approaches to features extraction typically require a user to manually identify (i.e., outline and fill) the features that are to be extracted within an image manipulation software program. The amount of time required to perform feature based manipulation of graphic images increases with the quantity and types of features contained in the image.
For example, extracting the windows from an image of a single house takes significantly less time than identifying the windows from an image of a city street having multiple buildings and performing manipulations based on the identified windows. More features require more time because the user must detect or identify each feature individually.
The typical efficiency short-cut, “copy and paste,” provides some help to the user, especially when the features are uniform. However, each pasted area must still be individually placed upon the corresponding feature's content as expressed in an image. Further, this usefulness is significantly reduced when the features lie on varying planes of perspective (i.e., a copy of an extraction area for a front-facing window will not match that of a side-facing window).